UK to Pursue Independent Path on AI Regulation, Says Starmer

UK Prime Minister Keir Starmer announced that Britain will establish its own approach to artificial intelligence (AI) regulation, setting it apart from other nations’ strategies. During a statement on Monday, Starmer emphasized that while various countries are adopting different frameworks, the UK now has full control over its regulatory landscape.

“We will go our own way on this,” Starmer declared, asserting the country’s autonomy in crafting AI rules. He added that the UK would thoroughly test and understand AI technologies before implementing regulations. This approach aims to ensure that when regulation does occur, it will be “proportionate and grounded.”

HCLTech Misses Q3 Revenue Estimate, Tightens Full-Year Forecast

India’s third-largest software company, HCLTech, reported a smaller-than-expected revenue for the December quarter and revised its full-year growth forecast downwards. Despite an increase in demand anticipated for fiscal 2025, underperformance in its software business led to the company narrowing its revenue growth prediction.

Revenue and Forecast Adjustments

HCLTech’s consolidated revenue for Q3 rose by 5.1%, reaching 298.9 billion rupees ($3.45 billion), but this fell short of analysts’ expectations, which were pegged at 300.68 billion rupees. As a result, the company tightened its full-year revenue growth forecast for fiscal 2025 to 4.5%-5%, down from a previous range of 3.5%-5%. The revision reflects the completion of an acquisition of certain intellectual property (IP) assets from U.S.-based HP Enterprise last month.

Challenges in Software Business

The company’s software vertical, which constitutes 11% of total revenue, underperformed expectations. However, CEO C Vijayakumar noted an improvement in the demand environment, especially in discretionary spending, which is expected to pick up in 2025. He emphasized that clients are looking to increase their IT investments in the coming year, providing some optimism for future growth.

Profit and Deal Wins

Despite the revenue miss, HCLTech reported a 5.5% increase in net profit, which reached 45.91 billion rupees, slightly above analysts’ expectations of 45.82 billion rupees. The company also secured new deal wins worth $2.1 billion in Q3, a solid result despite a slight decline from the previous quarter ($2.22 billion) and a year-over-year increase from $1.93 billion.

Industry Outlook and Comparison

HCLTech is not alone in facing challenges in India’s tech industry, which has been experiencing slower growth due to inflationary pressures and macroeconomic uncertainty. Analysts expect U.S. President-elect Trump’s pro-business policies to benefit Indian IT firms, as the North American market accounts for a significant portion of the sector’s revenue.

Shares of market leader Tata Consultancy Services (TCS) surged 5.6% last Friday after signaling a possible demand revival, even though it missed Q3 estimates. HCLTech’s stock closed 0.3% lower ahead of its earnings report. Other major Indian IT companies, including Wipro and Infosys, are expected to release their quarterly results later this week.

 

US Implements New AI Chip Regulation to Control Global Access

The U.S. government has introduced a new regulation to restrict global access to U.S.-designed artificial intelligence (AI) chips and technology. This regulation targets the export of advanced graphics processing units (GPUs), essential for building AI models, and aims to ensure that cutting-edge AI capabilities are developed and deployed securely and in trusted environments.

Which Chips Are Restricted?

The regulation focuses on GPUs, which were initially created to accelerate graphics rendering but have become critical for AI due to their ability to process large amounts of data simultaneously. U.S. companies, particularly Nvidia, dominate the production of these chips. GPUs like Nvidia’s H100 are used extensively in training advanced AI models, such as OpenAI’s ChatGPT.

What Is the U.S. Doing?

To regulate global access, the U.S. is extending restrictions on advanced GPUs, specifically those used in AI training clusters. The new rule sets limits based on compute power, measured by Total Processing Performance (TPP). For most countries, the cap is set at 790 million TPP until 2027, equivalent to roughly 50,000 H100 GPUs. These restrictions are meant to control access to the computing power required for large-scale AI research and applications.

However, certain companies, like Amazon Web Services and Microsoft Azure, that meet the requirements for special authorizations (called “Universal Verified End User” status) are exempt from these caps. Additionally, countries with “national Verified End User” status are allowed more advanced GPUs—about 320,000 over the next two years.

Exceptions to Licensing

There are exceptions for small GPU orders, such as those for universities or research institutions. Orders that do not exceed 1,700 H100 chips only require government notification and do not count toward the caps. This exception is designed to facilitate the global flow of AI technology for low-risk purposes.

GPUs intended for gaming are also excluded from the restrictions, ensuring that the gaming sector remains unaffected by the new rules.

Which Places Can Get Unlimited AI Chips?

Eighteen countries are exempt from the country-specific caps on GPUs. These countries include the U.S., Australia, Canada, Japan, South Korea, the European Union members, and Taiwan. This list reflects nations the U.S. considers aligned in terms of AI development and security.

What Is Being Done with ‘Model Weights’?

In addition to GPUs, the U.S. is regulating “model weights,” which are numerical parameters used in training AI models. These model weights, essential for refining the performance of AI algorithms, are considered sensitive information. The new rule establishes security measures to protect these parameters, ensuring that only trusted entities manage the most advanced AI systems.

Conclusion

The U.S. regulation reflects growing concerns over AI technology’s potential misuse and aims to ensure its responsible development. By controlling the flow of critical AI resources like GPUs and model weights, the U.S. seeks to maintain dominance in the AI field while preventing sensitive technology from reaching adversarial nations.